





'''simple docstring'''


from ...configuration_utils import PretrainedConfig
from ...utils import logging


a__			:					Union[str, Any]       						=						logging.get_logger(__name__)

a__			:					List[Any]       						=						{
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}






class     lowerCAmelCase__ (				UpperCAmelCase_    ):

       '''simple docstring'''
       _lowerCamelCase								="biogpt"

       def __init__( self					:				Union[str, Any]       ,     a__					:				List[Any]=42384       ,     a__					:				List[Any]=1024       ,     a__					:				Optional[Any]=24       ,     a__					:				Tuple=16       ,     a__					:				str=4096       ,     a__					:				int="gelu"       ,     a__					:				List[str]=0.1       ,     a__					:				List[str]=0.1       ,     a__					:				Any=1024       ,     a__					:				Dict=0.02       ,     a__					:				Any=1e-1_2       ,     a__					:				Union[str, Any]=True       ,     a__					:				Tuple=True       ,     a__					:				Optional[Any]=0.0       ,     a__					:				Tuple=0.0       ,     a__					:				List[Any]=1       ,     a__					:				Tuple=0       ,     a__					:				List[str]=2       ,     **a__					:				Any       ,     ):
              UpperCAmelCase  =						vocab_size
              UpperCAmelCase  =						max_position_embeddings
              UpperCAmelCase  =						hidden_size
              UpperCAmelCase  =						num_hidden_layers
              UpperCAmelCase  =						num_attention_heads
              UpperCAmelCase  =						intermediate_size
              UpperCAmelCase  =						hidden_act
              UpperCAmelCase  =						hidden_dropout_prob
              UpperCAmelCase  =						attention_probs_dropout_prob
              UpperCAmelCase  =						initializer_range
              UpperCAmelCase  =						layer_norm_eps
              UpperCAmelCase  =						scale_embedding
              UpperCAmelCase  =						use_cache
              UpperCAmelCase  =						layerdrop
              UpperCAmelCase  =						activation_dropout
              super().__init__(pad_token_id=a__       ,     bos_token_id=a__       ,     eos_token_id=a__       ,     **a__						)










'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCAmelCase        =							{"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase        =							["GLPNFeatureExtractor"]
  __lowerCAmelCase        =							["GLPNImageProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __lowerCAmelCase        =							[
      "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
      "GLPNForDepthEstimation",
      "GLPNLayer",
      "GLPNModel",
      "GLPNPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_glpn import GLPNFeatureExtractor
    from .image_processing_glpn import GLPNImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_glpn import (
        GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
        GLPNForDepthEstimation,
        GLPNLayer,
        GLPNModel,
        GLPNPreTrainedModel,
    )


else:
  import sys

  __lowerCAmelCase        =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




